1. Field of the Invention
The invention described herein is related to user location determination via the reception of electromagnetic signals. More specifically, the invention is related to determining the location of an addressable receiver in a wireless communication network, such as an IEEE 802.11 compliant wireless local area network.
2. Description of the Prior Art
Recent trends in wireless communication, computer networking, and information dispersal have given rise to the field of ubiquitous or pervasive computing. Ubiquitous computing allows the use of a plurality of computing devices positioned throughout a physical environment, but the access to a particular computer is essentially invisible to the user. Ideally, a person would continually interact with hundreds of nearby wirelessly interconnected computers. A user would be able to access the computer network, or rather the computer network could access the user, via a small computing device somewhere on the user's person. It has been envisioned that such a computing device may be incorporated into everyday items, even pieces of clothing.
As ubiquitous computing gains popularity, the need for context-aware applications is steadily increasing. One of the most important pieces of contextual information is the location of the user, with which the network can provide location-specific information and services.
Many systems over the years have tackled the problem of determining and tracking user position. One of the most popular, the global positioning satellite (GPS) system, is very useful in outdoor situations. However, the line-of-sight to GPS satellites is unavailable inside buildings and hence the GPS system cannot be used indoors.
Locating users in a wide-area cellular-based network has been motivated in recent years by the Federal Communication Commissions 94-102 Order, mandating the automatic location of 911 callers on a cellular phone. The two most widely known location technologies used in the wide-area cellular-based systems are time difference of arrival (TDOA) and angle of arrival (AOA). TDOA systems make use of the principle that an emitter location can be estimated by the intersection of hyperbolae of constant differential times-of-arrival of the signals at two or more pairs of base stations. AOA systems use simple triangulation based on an estimated angle of arrival of a signal at two or more base stations so as to estimate the location of a desired transmitter. While these systems are promising in outdoor environments, their effectiveness in indoor environments is limited by the multiple reflections suffered by the electromagnetic radiation, which leads to an inaccurate estimate of the time of arrival or angle of arrival.
Many infrared (IR) based systems have been proposed and are presently in use. In the Active Badge Location System, a badge worn by a person emits a unique IR signal which it relays to fixed IR receivers. The received signal is processed by a location manager software package to determine the location of the badge. However, if the walls of a room block the IR signal, the user cannot be accurately located within the blocked area. IR based location techniques also suffer from limited range, poor performance in the presence of direct sunlight, and significant installation and maintenance costs.
Magnetic tracking has been used to support virtual reality and motion capture for computer animation. These tracking systems generate axial DC magnetic field pulses from a transmitting antenna in a fixed location. The system computes the position and orientation of the receiving antennas by measuring the response in three axes orthogonal to the transmitter pulse. Such systems suffer from steep implementation costs and the requirement of tethering the tracked object to a control unit. Moreover, the sensors must remain within 1-3 meters of the transmitter and positional accuracy degrades with the presence of metallic objects in the environment.
Several RF-based location determination techniques have become the subject of recent research. The Active Bat system is based on combining RF and ultrasonic technologies. A short pulse of ultrasonic energy is emitted from a transmitter (the Bat) attached to the object to be located in response to an RF request from a local controller. The local controller sends, at the same time as the request packet, a synchronized reset signal to ceiling sensors using a wired serial network. The system measures the times-of-flight of the ultrasonic pulse to the mounted receivers on the ceiling, using the speed of sound in air to calculate the distances from the Bat to each receiver. The local controller forwards these distances to a central controller that performs the location determination computation. The lack of scalability, difficulty in deployment, and high equipment costs are disadvantages to this approach.
The Cricket location support system also uses a combination of RF and ultrasound technologies to provide a location-support service to users and applications. Wall- and ceiling-mounted beacons are spread throughout a building, and information is transmitted on an RF signal operating at 418 MHz. With each RF transmission, an ultrasonic pulse is transmitted concurrently therewith. Listening devices await the RF signal and, upon receipt of the first few bits, listen for the corresponding ultrasonic pulse. When the ultrasonic pulse arrives, the listeners run maximum-likelihood estimators to correlate RF and ultrasound samples to obtain a distance estimate. Once again, the requirement of specialized hardware and poor scalability of this system prevent the widespread use of this application.
In the last few years, many techniques have been proposed to provide user location services in an RF-based system that does not require additional hardware. The RADAR system uses an RF signal strength as an indication of the distance between the transmitter and receiver. During an offline phase, the system builds a radio map for the RF signal strength from a fixed number of receivers. During normal operation, the RF signal strength of the transmitter is measured by a set of fixed receivers and is sent to a central controller. The central controller uses a K-nearest approach to determine the location from the radio map that best fits the collected signal strength information.
The TMI system is based on triangulation, mapping, and interpolation (TMI). In the TMI technique, the physical position of all the access points in the area must be known and a function to map signal strength into distances is required. The system generates a set of training points at each trained position. The interpolation of the training data allows the algorithm to use less training data. During user location determination, the system uses the approximate function derived from the training data to generate contours and the calculated intersections between different contours yields the signal space position of the user. The nearest set of mappings from the signal space to the physical space is found by applying a weighted average, based on proximity, to the signal position.
The Nibble location system from UCLA uses a Bayesian network to infer a user location. The Bayesian network model includes nodes for location, noise, and access points (sensors). The signal-to-noise ratio (SNR) observed from an access point at a given location is taken as an indication of that location. The system also quantizes the SNR into four levels: high, medium, low, and none. However, the Nibble location system stores the joint distribution between all of the random variables of this system, which increases the amount of computation necessary and degrades system scalability.
It is apparent from the foregoing discussions of the prior art that there exists a need for a user location determination method that can be implemented without the need for additional hardware and utilizes techniques to improve spatial resolution, while at the same time, reducing the computational cost. Reducing the number of computations ultimately reduces the amount of energy required to determine a location. This is of interest in that many of the components of a ubiquitous computing system are battery-powered.